Guide To Developing High-Quality, Reliable, and Valid Multiple-Choice Assessments
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High Resolution Image Download MS PowerPoint Slide Chemistry faculty members are highly skilled in obtaining, analyzing, and interpreting physical measurements, but often they are less skilled in measuring student learning. This work provides guidance for chemistry faculty from the research literature on multiple-choice item development in chemistry. Areas covered include content, stem, and response construction; item analysis; item difficulty; and item discrimination. The goal is to help faculty construct high-quality, reliable, and valid multiple-choice items to evaluate students’ ability to meet learning objectives and to demonstrate proficiency in the content domain under study. Using item-writing guidelines based upon the research literature allows faculty to create assessments that are reliable and valid, with greater ability to discriminate between high- and low-achieving students.
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Multiple-choice question tests are one of the most popular types of assessment in education.
“Multiple-choice question (MCQ) tests are one of the most popular types of assessment in education [3, 52].”
From A Comparative Study of AI-Generated (GPT-4) and Human-crafted MCQs in Programming Education (2024) · cites this paper as [52]
Cites
A Review of Multiple-Choice Item-Writing Guidelines for Classroom Assessment
Haladyna, T. M., Downing, S. M., & Rodriguez, M. C. (2002) · Applied Measurement in Education · doi:10.1207/s15324818ame1503_5 · Cited by 973 · see citing works
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Characterizing College Science Assessments: The Three-Dimensional Learning Assessment Protocol
Laverty, J. T., Underwood, S. M., Matz, R. L., Posey, L. A., Carmel, J. H., Caballero, M. D., Fata-Hartley, C. L., Ebert-May, D., Jardeleza, S. E., & Cooper, M. M. (2016) · PLOS ONE · doi:10.1371/journal.pone.0162333 · Cited by 262 · see citing works
A Comparative Study of AI-Generated (GPT-4) and Human-crafted MCQs in Programming Education
Doughty, J., Wan, Z., Bompelli, A., Qayum, J., Wang, T., Zhang, J., Zheng, Y., Doyle, A., Sridhar, P., Agarwal, A., et al. (2024) · Proceedings of the 26th Australasian Computing Education Conference · doi:10.1145/3636243.3636256 · Cited by 132 · see citing works
- Authors
- Towns, M. H.
- Affiliations
- Purdue University West Lafayette (US)
- Corresponding author
- Towns, Marcy H.
- ORCID
- Towns, Marcy H.
- Venue
- Journal of Chemical Education
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-07-31
- Volume
- 91
- Issue
- 9
- Pages
- 1426-1431
- ISSN
- 0021-9584 (ISSN-L)
- 1938-1328
- OpenAlex
- W1989277800
- Cited by
- 113
- References
- 1
- Citations by year
- 2026: 13 · 2025: 6 · 2024: 14 · 2023: 9 · 2022: 5 · 2021: 12 · 2020: 21 · 2019: 14 · 2018: 6 · 2017: 3 · 2016: 4 · 2015: 4 · 2014: 2
- FWCI
- 22.26
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Chemical Education (publishedVersion, other-oa)
- Topics
- Social Sciences › Education › Educational Assessment and Pedagogy
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Education › Student Assessment and Feedback
- Keywords
- chemistry assessment, item writing guidelines, item difficulty, item discrimination, item analysis, test reliability, test validity, learning objectives, chemistry faculty
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